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Boost Audio - Stem Splitter

boost_audio_stem_splitter

Split a song into separate stems with Boost Audio AI: vocals, drums, bass and other (4-stem mode). Ultimate plan unlocks a 6-stem mode with separate guitar and piano. Use this when the user wants individual instrument stems.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoStem separation mode. 6-stem requires Ultimate plan.4-stem
audio_urlNoOptional public URL to an audio/video file. If omitted, the user uploads the file in the rendered widget.
file_nameNoOriginal file name. Required when audio_base64 is provided.
file_typeNoOriginal mime type. Required when audio_base64 is provided.
file_tokenNoToken for a pre-uploaded large file (>22 MB). Obtained from POST /widget-api/upload-raw. Used instead of audio_base64 for large files.
audio_base64NoOptional base64-encoded audio file payload. Used by the widget when the host iframe blocks CORS fetches.

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With annotations already indicating readOnlyHint=false and destructiveHint=false, the description adds valuable context about plan requirements ('Ultimate plan unlocks a 6-stem mode') and the difference in output stems. No contradiction with annotations. It does not detail all side effects (e.g., upload limits, processing time), but adds sufficient behavior beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core action and outputs. Every clause is relevant, including the plan note and usage hint. No redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, but the description implies the result (separate stems) by stating the purpose. It covers the main workflow and mentions the plan limitation. Lacks explicit details on how results are delivered, but is adequate for a moderately complex tool with rich input schema descriptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description enriches the 'mode' parameter by explaining what 4-stem vs 6-stem yields ('separate guitar and piano'), which is not fully captured in the schema's enum description. This adds practical meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Split' and clearly identifies the resource ('a song into separate stems') with explicit outputs (vocals, drums, bass, other). It also distinguishes from sibling tools by stating 'Use this when the user wants individual instrument stems.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context for when to use the tool: 'Use this when the user wants individual instrument stems.' It does not explicitly mention alternatives or exclusions, but the context is specific and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a unique audio processing task (e.g., BPM/key detection, format conversion, stem splitting) with no functional overlap, ensuring agents can easily distinguish between them.

Naming Consistency5/5

All tool names follow a strict `boost_audio_verb_noun` pattern in snake_case, providing a predictable and clean naming convention across the entire set.

Tool Count5/5

With exactly 8 tools, the server is well-scoped for an audio processing domain—comprehensive enough to cover key tasks without being overwhelming or sparse.

Completeness4/5

The tools cover essential audio operations (conversion, extraction, generation, splitting, trimming, etc.), but a merging or concatenation tool is missing, leaving a minor gap.

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